A LIDAR system employs pulses of light to measure distance to an object based on the time of flight (TOF) of each pulse of light. A pulse of light emitted from a light source of the LIDAR system interacts with a distal object. A portion of the light reflects from the object and returns to a detector of the LIDAR system. Based on the time elapsed between emission of the pulse of light and detection of the returned pulse of light, a distance is estimated. In some examples, pulses of light are generated by a laser emitter. The light pulses are focused through a lens or lens assembly. The time it takes for a pulse of laser light to return to a detector mounted near the emitter is measured and a distance is derived from the time measurement with high accuracy.
Some LIDAR systems employ a single laser emitter/detector combination combined with a rotating mirror to effectively scan across a plane. Distance measurements performed by such a system are effectively two dimensional (i.e., planar), and the captured distance points are rendered as a 2-D (i.e., single plane) point cloud. In some examples, rotating mirrors are rotated at very fast speeds (e.g., thousands of revolutions per minute).
However, in many operational scenarios, a 3-D point cloud is required. A number of schemes have been employed to interrogate the surrounding environment in three dimensions. In some examples, a 2-D instrument is actuated up and down and/or back and forth, often on a gimbal. This is commonly known within the art as “winking” or “nodding” the sensor. Thus, a single beam LIDAR unit can be employed to capture an entire 3-D array of distance points, albeit one point at a time. In a related example, a prism is employed to “divide” the laser pulse into multiple layers, each having a slightly different vertical angle. This simulates the nodding effect described above, but without actuation of the sensor itself.
In all the above examples, the light path of a single laser emitter/detector combination is somehow altered to achieve a broader field of view. But, the number of pixels such devices can generate per unit time is inherently limited due to limitations on the pulse repetition rate of a single laser. Any alteration of the beam path to achieve a larger coverage area, whether it is by mirror, prism, or actuation of the device, comes at a cost of decreased point cloud density.
As noted above, 3-D point cloud systems exist in several configurations. However, in many applications it is necessary to collect distance measurements over a broad field of view. For example, in an autonomous vehicle application, the vertical field of view should extend down to the ground in front of the vehicle. In addition, the vertical field of view should extend above the horizon, in the event the car enters a dip in the road. In addition, it is necessary to have a minimum of delay between the actions happening in the real world and the imaging of those actions. In some examples, it is desirable to provide a complete image update at least five times per second. To address these requirements, a 3-D LIDAR system has been developed that includes an array of multiple laser emitters and detectors. This system is described in U.S. Pat. No. 7,969,558 issued on Jun. 28, 2011, the subject matter of which is incorporated herein by reference in its entirety.
In many applications, a sequence of pulses is emitted. The direction of each pulse is sequentially varied in rapid succession. In these examples, a distance measurement associated with each individual pulse can be considered a pixel, and a collection of pixels emitted and captured in rapid succession (i.e., “point cloud”) can be rendered as an image or analyzed for other reasons (e.g., detecting obstacles). In some examples, viewing software is employed to render the resulting point clouds as images that appear three dimensional to a user. Different schemes can be used to depict the distance measurements as 3-D images that appear as if they were captured by a live action camera.
In some examples, the timing of successive light emission pulses is set such that the return signal associated with a particular pulse emission is detected before the subsequent pulse emission is triggered. This ensures that a detected return signal is properly associated with the particular pulse emission that generated the detected return signal.
In some other examples, multiple pulses are emitted into the surrounding environment before a return signal from any of the multiple pulses is detected. Traditionally, this approach raises the potential for cross-talk among detected signals. In other words, when multiple pulses are emitted into the surrounding environment before a return signal from any of the multiple pulses is detected, a detected return signal might be incorrectly associated with a different pulse emission than the particular pulse emission that gave rise to detected return signal. This can potentially cause errors in distance measurement.
Traditionally, to avoid cross-talk among the multiple pulses, each of the multiple pulses is projected in a different direction. By projecting each of the multiple pulses in a different direction, each volume of space interrogated by each of the multiple pulses is completely separated from any volume of space interrogated by any of the other multiple pulses. As the separation among simultaneously interrogated spaces is increased, the likelihood of inducing measurement error due to cross-talk is reduced.
Whether sequential pulse techniques, or multiple pulse techniques with spatial separation are employed, performance challenges remain.
The detection of return signals includes significant sources of measurement noise. In some examples, a light pulse due to sun light, a solar flare or cosmic ray is detected and mistakenly associated with a particular pulse emission. This results in a false distance measurement. In some other examples, a pulse emission from another LIDAR system is detected and mistakenly associated with a particular pulse emission. Again, this results in a false distance measurement. These problems are exacerbated as measurement ranges are extended for a LIDAR system without increasing laser pulse intensity.
Existing LIDAR systems employ a single light pulse to interrogate a particular volume of the surrounding environment at any given time. These systems are prone to signal contamination from external noise sources such as sun light, cosmic rays or other LIDAR based imaging systems.
Improvements in noise rejection are desired to extend measurement range and reject detected signals associated with illumination sources not associated with the LIDAR system.